KINDI Center for Computing Research: المرسلات الحديثة
السجلات المعروضة 41 -- 60 من 297
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A meta-heuristic algorithm combined with deep reinforcement learning for multi-sensor positioning layout problem in complex environment
( Elsevier , 2025 , Article)In a multi-sensor positioning system (MSPS), the layout of sensors plays a crucial role in determining the system’s performance. Therefore, addressing the sensor layout problem (SLP) within the MSPS is an essential approach ... -
Wave energy forecasting: A state-of-the-art survey and a comprehensive evaluation
( Elsevier , 2025 , Article)Wave energy, a promising renewable energy source, has the potential to diversify the global energy mix significantly. Accurate forecasting of significant wave height (SWH) is crucial for enhancing the efficiency and ... -
Complementary Learning Subnetworks towards Parameter-Efficient Class-Incremental Learning
( Institute of Electrical and Electronics Engineers Inc. (IEEE) , 2025 , Article)In the scenario of class-incremental learning (CIL), deep neural networks have to adapt their model parameters to non-stationary data distributions, e.g., the emergence of new classes over time. To mitigate the catastrophic ... -
Underwater Acoustic Signal Denoising Algorithms: A Survey of the State of the Art
( Institute of Electrical and Electronics Engineers Inc. (IEEE) , 2025 , Article)Underwater acoustic signal (UAS) denoising is crucial for enhancing the reliability of underwater communication and monitoring systems by mitigating the effects of noise and improving signal clarity. The complex and dynamic ... -
Euclidean and Poincaré space ensemble Xgboost
( Elsevier , 2024 , Article)The Hyperbolic space has garnered attention for its unique properties and efficient representation of hierarchical structures. Recent studies have explored hyperbolic alternatives to hyperplane-based classifiers, such as ... -
Heteroscedastic ensemble deep random vector functional link neural network with multiple output layers for High Frequency Volatility Forecasting and Risk Assessment
( Elsevier , 2025 , Article)Accurate volatility forecasting is crucial for the efficient management of financial systems. However, the dynamic nature and significant variability in financial time series data pose substantial challenges to achieving ... -
Stacked Ensemble Deep Random Vector Functional Link Network with Residual Learning for Medium-Scale Time-Series Forecasting
( Institute of Electrical and Electronics Engineers Inc. (IEEE) , 2025 , Article)The deep random vector functional link (dRVFL) and ensemble dRVFL (edRVFL) succeed in various tasks and achieve state-of-the-art performance compared with other randomized neural networks (NNs). However, existing edRVFL ... -
Safety Score as an Evaluation Metric for Machine Learning Models of Security Applications
( Institute of Electrical and Electronics Engineers Inc. , 2020 , Article)Machine learning studies have traditionally used accuracy, F1 score, etc. to measure the goodness of models. We show that these conventional metrics do not necessarily represent risks in security applications and may result ... -
Damping-Assisted Evolutionary Swarm Intelligence for Industrial IoT Task Scheduling in Cloud Computing
( Institute of Electrical and Electronics Engineers Inc. , 2024 , Article)Advancements in the Industrial Internet of Things (IIoT) have yielded massive volumes of data, taxing the capabilities of cloud computing infrastructure. Allocating limited computing resources to numerous incoming requests ... -
Ensemble Deep Random Vector Functional Link Neural Network for Regression
( Institute of Electrical and Electronics Engineers Inc. , 2023 , Article)Inspired by the ensemble strategy of machine learning, deep random vector functional link (dRVFL), and ensemble dRVFL (edRVFL) has shown state-of-The-Art results on different datasets. Our present work first fills the gap ... -
Kernel-Ridge-Regression-Based Randomized Network for Brain Age Classification and Estimation
( Institute of Electrical and Electronics Engineers Inc. , 2024 , Article)Accelerated brain aging and abnormalities are associated with variations in brain patterns. Effective and reliable assessment methods are required to accurately classify and estimate brain age. In this study, a brain age ... -
Self-Distillation for Randomized Neural Networks
( Institute of Electrical and Electronics Engineers Inc. , 2023 , Article)Knowledge distillation (KD) is a conventional method in the field of deep learning that enables the transfer of dark knowledge from a teacher model to a student model, consequently improving the performance of the student ... -
Neuro-Fuzzy Random Vector Functional Link Neural Network for Classification and Regression Problems
( Institute of Electrical and Electronics Engineers Inc. , 2024 , Article)The random vector functional link (RVFL) neural network has shown the potential to overcome traditional artificial neural networks' limitations, such as substantial time consumption and the emergence of suboptimal solutions. ... -
Online ensemble deep random vector functional link for the assistive robots
( Institute of Electrical and Electronics Engineers Inc. , 2023 , Conference)Active upper limb assistive robots have the potential to improve the quality of life for patients with limb disabilities and assist those who require rehabilitation. However, patients often have difficulty accepting these ... -
Echo state neural network based ensemble deep learning for short-term load forecasting
( Institute of Electrical and Electronics Engineers Inc. , 2022 , Conference)Precise electricity load forecasts assist in planning, maintaining, and developing power systems. However, the electricity load's un-stationary and non-linear characteristics impose substantial challenges in anticipating ... -
Ensemble Deep Random Vector Functional Link Neural Network Based on Fuzzy Inference System
( Institute of Electrical and Electronics Engineers Inc. , 2024 , Article)The ensemble deep random vector functional link (edRVFL) neural network has demonstrated the ability to address the limitations of conventional artificial neural networks. However, since edRVFL generates features for its ... -
Multimodal Neuroimaging Based Alzheimer's Disease Diagnosis Using Evolutionary RVFL Classifier
( Institute of Electrical and Electronics Engineers Inc. , 2023 , Article)Alzheimer's disease (AD) is one of the most known causes of dementia which can be characterized by continuous deterioration in the cognitive skills of elderly people. It is a non-reversible disorder that can only be cured ... -
Online Continual Learning for Control of Mobile Robots
( Institute of Electrical and Electronics Engineers Inc. , 2023 , Conference)This work presents a novel approach which integrates deep learning, online learning and continual learning paradigms for adaptive control for robotic systems. Deep learning allows generalising knowledge about the robot, ... -
3-sCHSL: Three-Stage Cyclic Hybrid SFS and L-SHADE Algorithm for Single Objective Optimization
( Institute of Electrical and Electronics Engineers Inc. , 2023 , Conference)This paper proposes a novel hybridization of two metaheuristic algorithms to solve the real-parameter single objective numerical optimization problems. The proposed Three-stage Cyclic Hybrid SFS and L-SHADE (3-sCHSL) ... -
Weighted Kernel Ridge Regression based Randomized Network for Alzheimer's Disease Diagnosis using Susceptibility Weighted Images
( Institute of Electrical and Electronics Engineers Inc. , 2023 , Conference)Alzheimer's disease (AD) is a neurological disorder that primarily affects the elderly and is characterized by cognitive decline and memory loss. Recent research has shown that susceptibility-weighted imaging (SWI) images ...
